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Record W6989558657

Borrowers and Bullies

2022· dissertation· en· W6989558657 on OpenAlexaboutno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicPosthumanist Ethics and Activism
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionWork (physics)SubjectivitySet (abstract data type)DirtHabitInvisibility
DOInot available

Abstract

fetched live from OpenAlex

Borrowers and Bullies is an exhibition of sculpture, installation, and video. I was highly impacted throughout the making of this work by the Covid-19 pandemic, which began immediately preceding my acceptance into the UW MFA program and has endured to the present at the time of writing. By walking the same paths daily, in my home and in the park behind my home, I more clearly saw my own habits in settler-colonial greenspaces and the built environment. \n \nCentral to this work is my understanding of a habit as not just a set of repeated behaviours but as a central, life-configuring scaffold for building and maintaining relationships to one another, the built environment, and the land. During the summer of 2021, my collaborative partner and I harvested materials, documentation, and experiences from settler-colonial greenspaces in Southern Ontario and The Maritimes, while asking myself: How does my social muscle memory inform how I understand my home, my neighbourhood, my nation? And do these habits inform my ethics? \n \nI see my collaborative art practice as an opportunity to manifest anti-colonial and anti-capitalist ethics by tugging at relationships between subjectivity and materiality. Borrowers and Bullies is an exhibition with its eyes turned to the colonial-capitalist enclosure of time and land, and how that enclosure configures the knowable, the thinkable, and the imaginable. \n \nThis exhibition, Borrowers and Bullies, is a document of work that took place in very interior spaces. What is in the gallery is residue from the work embedded in my body and my collaborator’s; I proceed from this thesis work transformed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0110.006
Scholarly communication0.0080.007
Open science0.0010.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0790.007

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.247
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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